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at the intersection of numerical linear algebra and advanced HPC. The candidate will join an international environment, with opportunities to collaborate with experts from the USA, and KAUST and publish in top-tier
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to the large-scale nature, complexity, and heterogeneity of 6G networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal
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demonstrating a proof of concept for low-power logic gates based on spin waves. The work involves experimental research. The post-doc will be responsible for: - the growth and optimization of magnetic thin films
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project aimed at utilizing 3D physics-based wave propagation simulations up to 10 Hz to improve ground motion estimates in urbanized areas in California. The central goals are to unify and optimize
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[map ] Subject Area: Applied and Numerical Analysis Appl Deadline: 2025/09/15 11:59PM (posted 2025/08/05, listed until 2025/12/31) Position Description: Apply Position Description Doctoral and
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” focusing on the effect of a fluctuating environment on the collective dynamics of self-propelled agents, a numerical part on “reinforcement learning” focusing on optimizing communication between agents in a
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quite heavily. We establish new results concerning the analysis of stochastically driven anisotropic fluids, design novel numerical simulation and optimal control schemes, and provide new means for risk
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 1 month ago
Job description:Postdoc (f/m/d) AI-based automated adaptation and biological optimization of proton therapy With cutting-edge research in the fields of ENERGY, HEALTH and MATTER, around 1,500 employees
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) for municipalities; Optimizing building-level energy demand and supply Extend and customize the frameworks according to the research questions and project needs. Conduct scenario analyses to explore pathways
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, their modelling through mathematics and numerical simulations, and their control and optimization. Our belief is that a proper understanding of systems requires a modelling step, which allows to identify causal